The AI infrastructure conversation has largely been defined by compute, but new global research from IDC reveals another critical factor organizations must address as they scale AI: data that persists and compounds long after individual compute cycles are complete. The IDC White Paper, Built for Scale: The Enduring Role of HDDs in the AI Era, sponsored by WD, finds that AI is creating a structural expansion in data storage requirements, with organizations generating more data, assigning greater value to it, retaining it longer, and increasingly bringing historical data back online for new AI workloads.
The research finds AI requires data and increases the potential value of data already stored, creating a compounding data cycle. While compute requirements vary by workload, data created by AI persists and accumulates, making storage capacity, accessibility and economics increasingly critical.
AI is driving rapid data growth across the lifecycle, from training datasets and model checkpoints to inference outputs, logs and synthetic data. Among surveyed organizations, 59.4% identified AI-generated data including synthetic data, inference outputs and model logs as the leading driver of data lake growth. As a result, 96% anticipate needing faster archive retrieval to support AI inference and retrieval-augmented generation applications.
Data is persisting longer, becoming more active and valuable as historical data reenters the active lifecycle. Traditional boundaries between active and archived data are changing as information that once sat dormant becomes valuable input for AI workloads.
AI infrastructure must be designed for the full data lifecycle, balancing performance, capacity, accessibility and economics according to workload requirements. At AI scale, where data lives and what it costs to store and access becomes a critical architectural consideration.
"For the last few years, the AI infrastructure conversation has centered on compute. But AI runs on data," said Irving Tan, CEO, WD. "Organizations are generating more data, keeping it longer, and finding new ways to create value from the information they already have. Compute requirements will evolve over time, but the need to store, manage and access data at scale is only growing. That foundation will play a critical role in determining how far AI can go."
About WD
WD, also known as Western Digital, builds the storage infrastructure that powers certainty in the AI-driven data economy. At the forefront of innovation, WD partners with the world's leading hyperscalers, cloud service providers, and enterprises to enable reliable storage solutions that are proven and trusted at scale. Driven by a culture of innovation and execution, WD helps customers store, protect, and use the world's data with confidence.
